fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of r-owidapi and rfm — release velocity, themes, recent moves, and the top alternatives to consider.
The R client for Our World in Data found its search had been reading a tenth of the catalog.
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
A customer segmentation package that went quiet for six years and returned with dependency hygiene
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
owidapi is a small R client for Our World in Data, covering chart data retrieval, metadata, the full chart catalog, and search over it, with experimental Shiny output helpers. It is three releases old and the most recent one is almost entirely repair: the catalog function was silently truncating at 1000 rows because of a Datasette row cap, which meant search had been operating on a fraction of what exists.
Development is about making a thin wrapper trustworthy against an upstream that moves without notice. The truncation fix pages through the catalog properly; a separate fix stops the function breaking when Our World in Data dropped a column, by parsing typed columns only when present. Tests moved to mocked responses, with a small live suite retained purely to detect schema drift and skipped on CRAN — a sensible design for a package whose main risk is that the API changes shape rather than that the code is wrong. The user-facing surface has not grown since the initial release; the work is in defending it.
On this pattern the next release is likelier to be another upstream-compatibility fix than new functionality, with the schema-drift tests the mechanism that surfaces it.
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
The 0.4.0 release says more about maintenance posture than about product direction — the version jump past 0.3.x with only two bug fixes and a dependency reshuffle suggests a package being brought back to a releasable state rather than resuming development. Promoting plotly and gganimate to Imports makes the visualization stack mandatory, which is a heavier install in exchange for a simpler code path. The core RFM computation itself has not changed in this window.
The entries show a package returning from dormancy rather than pursuing a roadmap, so further small fixes are more likely than new segmentation capability.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either r-owidapi or rfm.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
State-space data simulation for R, filled in one function at a time
See all r-owidapi alternatives → · See all rfm alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. r-owidapi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. r-owidapi is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top r-owidapi alternatives in Analytics are ranked by recent ship velocity. Browse the "r-owidapi alternatives" section above for the current picks, or visit /alternatives/r-owidapi for the full list with editorial commentary on each.
Top rfm alternatives in Analytics are ranked by recent ship velocity. Browse the "rfm alternatives" section above for the current picks, or visit /alternatives/rfm for the full list with editorial commentary on each.